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Comparison of 1D and 3D Models for the Estimation of Fractional Flow Reserve
In this work we propose to validate the predictive capabilities of one-dimensional (1D) blood flow models with full three-dimensional (3D) models in the context of patient-specific coronary hemodynamics in hyperemic conditions. Such conditions mimic the state of coronary circulation during the acqui...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6250665/ https://www.ncbi.nlm.nih.gov/pubmed/30467321 http://dx.doi.org/10.1038/s41598-018-35344-0 |
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author | Blanco, P. J. Bulant, C. A. Müller, L. O. Talou, G. D. Maso Bezerra, C. Guedes Lemos, P. A. Feijóo, R. A. |
author_facet | Blanco, P. J. Bulant, C. A. Müller, L. O. Talou, G. D. Maso Bezerra, C. Guedes Lemos, P. A. Feijóo, R. A. |
author_sort | Blanco, P. J. |
collection | PubMed |
description | In this work we propose to validate the predictive capabilities of one-dimensional (1D) blood flow models with full three-dimensional (3D) models in the context of patient-specific coronary hemodynamics in hyperemic conditions. Such conditions mimic the state of coronary circulation during the acquisition of the Fractional Flow Reserve (FFR) index. Demonstrating that 1D models accurately reproduce FFR estimates obtained with 3D models has implications in the approach to computationally estimate FFR. To this end, a sample of 20 patients was employed from which 29 3D geometries of arterial trees were constructed, 9 obtained from coronary computed tomography angiography (CCTA) and 20 from intra-vascular ultrasound (IVUS). For each 3D arterial model, a 1D counterpart was generated. The same outflow and inlet pressure boundary conditions were applied to both (3D and 1D) models. In the 1D setting, pressure losses at stenoses and bifurcations were accounted for through specific lumped models. Comparisons between 1D models (FFR(1D)) and 3D models (FFR(3D)) were performed in terms of predicted FFR value. Compared to FFR(3D), FFR(1D) resulted with a difference of 0.00 ± 0.03 and overall predictive capability AUC, Acc, Spe, Sen, PPV and NPV of 0.97, 0.98, 0.90, 0.99, 0.82, and 0.99, with an FFR threshold of 0.8. We conclude that inexpensive FFR(1D) simulations can be reliably used as a surrogate of demanding FFR(3D) computations. |
format | Online Article Text |
id | pubmed-6250665 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-62506652018-11-28 Comparison of 1D and 3D Models for the Estimation of Fractional Flow Reserve Blanco, P. J. Bulant, C. A. Müller, L. O. Talou, G. D. Maso Bezerra, C. Guedes Lemos, P. A. Feijóo, R. A. Sci Rep Article In this work we propose to validate the predictive capabilities of one-dimensional (1D) blood flow models with full three-dimensional (3D) models in the context of patient-specific coronary hemodynamics in hyperemic conditions. Such conditions mimic the state of coronary circulation during the acquisition of the Fractional Flow Reserve (FFR) index. Demonstrating that 1D models accurately reproduce FFR estimates obtained with 3D models has implications in the approach to computationally estimate FFR. To this end, a sample of 20 patients was employed from which 29 3D geometries of arterial trees were constructed, 9 obtained from coronary computed tomography angiography (CCTA) and 20 from intra-vascular ultrasound (IVUS). For each 3D arterial model, a 1D counterpart was generated. The same outflow and inlet pressure boundary conditions were applied to both (3D and 1D) models. In the 1D setting, pressure losses at stenoses and bifurcations were accounted for through specific lumped models. Comparisons between 1D models (FFR(1D)) and 3D models (FFR(3D)) were performed in terms of predicted FFR value. Compared to FFR(3D), FFR(1D) resulted with a difference of 0.00 ± 0.03 and overall predictive capability AUC, Acc, Spe, Sen, PPV and NPV of 0.97, 0.98, 0.90, 0.99, 0.82, and 0.99, with an FFR threshold of 0.8. We conclude that inexpensive FFR(1D) simulations can be reliably used as a surrogate of demanding FFR(3D) computations. Nature Publishing Group UK 2018-11-22 /pmc/articles/PMC6250665/ /pubmed/30467321 http://dx.doi.org/10.1038/s41598-018-35344-0 Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Blanco, P. J. Bulant, C. A. Müller, L. O. Talou, G. D. Maso Bezerra, C. Guedes Lemos, P. A. Feijóo, R. A. Comparison of 1D and 3D Models for the Estimation of Fractional Flow Reserve |
title | Comparison of 1D and 3D Models for the Estimation of Fractional Flow Reserve |
title_full | Comparison of 1D and 3D Models for the Estimation of Fractional Flow Reserve |
title_fullStr | Comparison of 1D and 3D Models for the Estimation of Fractional Flow Reserve |
title_full_unstemmed | Comparison of 1D and 3D Models for the Estimation of Fractional Flow Reserve |
title_short | Comparison of 1D and 3D Models for the Estimation of Fractional Flow Reserve |
title_sort | comparison of 1d and 3d models for the estimation of fractional flow reserve |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6250665/ https://www.ncbi.nlm.nih.gov/pubmed/30467321 http://dx.doi.org/10.1038/s41598-018-35344-0 |
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